scholarly journals Virtual screening approach to identifying influenza virus neuraminidase inhibitors using molecular docking combined with machine-learning-based scoring function

Oncotarget ◽  
2017 ◽  
Vol 8 (47) ◽  
pp. 83142-83154 ◽  
Author(s):  
Li Zhang ◽  
Hai-Xin Ai ◽  
Shi-Meng Li ◽  
Meng-Yuan Qi ◽  
Jian Zhao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Influenza Virus ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Scoring Function ◽  
Neuraminidase Inhibitors ◽  
Screening Approach ◽  
Influenza Virus Neuraminidase ◽  
Virtual Screening Approach

A multi-conformational virtual screening approach based on machine learning targeting PI3Kγ

2021 ◽  
Author(s):  
Jingyu Zhu ◽  
Yingmin Jiang ◽  
Lei Jia ◽  
Lei Xu ◽  
Yanfei Cai ◽  
...  
Keyword(s):  
Machine Learning ◽  
Virtual Screening ◽  
Screening Approach ◽  
Virtual Screening Approach

scholarly journals Simeprevir and Eltrombopag as Potential Inhibitors of SARS-CoV2 Proteases: A Molecular Docking and Virtual Screening Approach to Combat COVID-19

2020 ◽  
Author(s):  
Ananta Swargiary ◽  
AKALESH Verma ◽  
Manita Daimari ◽  
Mritunjoy Kumar Roy
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Binding Affinities ◽  
Screening Approach ◽  
Approved Drugs ◽  
Potential Inhibitors ◽  
Fda Approved Drugs ◽  
Virtual Screening Approach

The present study investigates the binding affinities of 61 FDA approved drugs against two key proteases of SARS-COV2, 3-chymotrypsin-like protease and papain-like protease. We also investigates the ADMET properties of the top 10 besting binding drugs to understand the drug likeness property.

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